Improving laboratory workforce efficiency using AI-assisted digital cytology within an HPV-based cervical screening programme: A model-based evaluation for the NHS Cervical Screening Programmes.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 42526933.
- Also identified by DOI 10.1136/bmjopen-2025-113298 and PMC identifier 13422948.
- Licence recorded as CC BY-NC.
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Abstract
We aimed to estimate the time required to review and report cervical cytology slides within a Human Papillomavirus (HPV)-primary cervical cancer screening programme, where cytology is used for triage following a positive HPV test, comparing Artificial Intelligence (AI)-assisted digital cytology (Genius) with manual microscopy. A decision-tree model of the flow of slides through the National Health Service (NHS) England cervical screening cytology laboratory workflow, parameterised using published evidence and expert input. Cytology laboratories within the NHS Cervical Screening Programme in England and Scotland. Screening and reporting 479,125 cytology slides annually in England was estimated to require 31,842 staff hours with AI-assisted digital cytology versus 103,151 hours with manual microscopy. The mean time per slide review and reporting was 4.0 vs 12.9 minutes, respectively, corresponding to a potential 69% increase in overall productivity. AI-assisted digital cytology can support more resilient cervical screening programmes in the UK and other countries by reducing staff time required for slide review and reporting. These findings may inform policymakers considering strategies to mitigate workforce shortages.
Medical subject headings
- Uterine Cervical Neoplasms
- Papillomavirus Infections
- Early Detection of Cancer
- Artificial Intelligence
- Mass Screening